Within the field of camera surveillance, it is often of interest to determine sharpness or acutance of images. To do this, a contrast value is often used, under the logic that if the contrast of an image is relatively high then the image is probably sharp. This method has several problems. One is that it does not take into the account that high contrast globally over the picture may not indicate a sharp image—an image where one part is very bright, such as an image containing the daytime sky, may have very high contrast without being particularly well-focused. Another problem is that an image which is half black and half white has the same amount of contrast as an image of a checkerboard, while the latter clearly has more defined features. A third problem is that image sensor noise may provide false contrast, for example, uniform areas may contain high and/or low pixel values generated by image sensor noise, creating a contrast value which is difficult to use for adjustment of camera settings as it is disjunct from actual features or objects imaged by the camera. Another problem is that optical effects due to lens configuration and other characteristics of the camera may cause the image to be for example darker in areas closer to the edge of the image, affecting the contrast of the image even without any objects being present in the image at all. For at least these reasons, a better way of determining the visual sharpness or acutance of an image is needed.